The background of this invention is classified by number 706—Data Processing with subject matter: Artificial Intelligence. Also, see Natural Language Processing (NLP). Prior work in the same area by the applicant includes: U.S. Pat. Nos. 6,101,490 and 6,269,356.
The said enclosed Patent Application comprises computer software running on computing systems using the Prolog computer language using hundreds of rules to process the English language. Users store English language sentences (their knowledge and link it to other knowledge) in defined databases that are selectable by letters, words, multiple words, symbols (i.e. $) synonyms, synonym sentences, symbol words, and one of more English language sentences. A symbol word is made from a concatenated word created by users and can be composed of letters, words, numbers, and symbols. The symbol word is stored as a word in a stored English language sentence and, as an example, can take the form of:
router1300d001CiscoOSJ350CXX1 is used for exch2000 at flr2011.
Where any letters in the above as in: OSJ350 or any derivation using the letters in sequence will sort other stored sentences such that when entering OSJ350 the sentence below is also shown (both sentences have OSJ350) in the above after mentioned stored sentence.OSJ350 is the Cisco operating system.One can see that by looking at the words in the stored sentence, the operating system OSJ350 runs on the Cisco router shown in the first stored sentence above. It also states that the computer router is used for the email exch2000 server and that server is located at floor location: flr2011. To find out where the exch2000 server is located, enter: flr2011 OR flr OR 2011 OR any sequential letters and numbers made up from the letters in the symbol word: flr2011 to get an associated stored sentence with these letters/numbers whose attachment shows a drawing that details where the exch2000 email server is located.
Help Desk systems do not have the known capability to allow users to store English language sentences and linkages with symbol words while also allowing the use of English language synonyms and English language synonym sentences. Often, data cannot be found because there are no symbol words and or they don't use synonyms in conjunction with symbol words. This method can be used on all types of systems to show relationships as expressed by stored English language sentences (knowledge), symbol words, synonyms, and synonym sentences remembering that stored sentences can have one of N other attachments (links) including other letters, words, synonyms, symbol words, and English language sentences. A synonym sentence is a sentence with different words that has the same attachment as one or more other sentences in the same database (preferable) or different database as learned by the computer.
Some examples of knowledge files consisting of the after mentioned methods, software, and computing systems includes but is not limited to (because the English language can describe any knowledge system and people use language to form actions and remember things by words) where the remembered things are words that can be part of a stored English language sentence and the actions are attachments (that can link to other user defined computer resources) and to the stored user English language sentence knowledge.
Typically, search engines and help systems don't let users store their own knowledge or use synonyms or symbol words in stored English language statements but rather may look at several documents (not stored by specific users) performing various rules test to return the data set which, in many cases, is too large to realistically view each item within the returned data set or most often returns data elements that are misleading. It may take several queries to find the right data contained within the search engine data set. However, one can store specific English language sentences that define a context and include synonyms and symbol words in order to improve on the ability to get the correct data on a first attempt. The context of each stored English language sentence can be customized to the needs of the user where as this cannot be automatically set by users who use commercial search engines. However, the context of each stored sentence can have as its attachment a search engine URL to open as specific web page or dynamically since the after mentioned application can compose words with synonyms or synonym sentences to send those words to a search engine. The stored English language words in the after mentioned application are the metadata (a system that uses data to describe other data) for the words stored on the internet. In fact, two or more stored sentences with different words can be attached to the same URL and these stored English language sentences are defined as synonym sentences. So where one user may think of words in one stored synonym sentence, another user may think of different words found in other stored synonym sentences to get to the same data. Each word or group of words for each stored sentence will connect to the same URL and will cause the after mentioned application to open the specific web page and if the set of input words is unique to the store sentences attached to the URL, the URL will automatically open when those letters/words are entered at the input of the said application. The said application serves as a massive integrator of knowledge that includes data on LANs, WANs, and other computing devices where an attachment is a link to any computer resource comprising computer programs URLs, and other English language sentences.
All processes within the said application are done by using English language sentences to switch to a different SQL database, to open a different text files (text files are used to open SQL databases), to open URLs, to execute computer programs, to run SQL queries on external SQL databases, to send English language text and symbols via agent software to other computers running the said application on the Internet, to link as attachments to other English language sentences by whole English language sentences, words, letters or multiples of each ending with a period or question mark character as by example: gmail. (car, automobile, vehicle as a synonym words). flr. Google what is the time in London, England? agentBill get me a map of local gas prices. Where each of the after mentioned letters, words, synonyms, symbol words, search engine sentences or agent software sentences can be composed and input to the said application or stored in a text file or SQL database and input to the said application as an attachment.
The said application is designed to use methods that substantially improve computer human language automation, to let users store their own knowledge using letters, words, synonyms and symbols words with English language sentences, to integrate knowledge from the Internet and user defined knowledge or other sources of knowledge in order to reduce the number of steps to get knowledge or improve on the quality of knowledge retrieved by users.
Materials used as references in the design of the after mentioned software application:
Prolog Programming in Depth—Michael A. Covington, Donald Nute, and Andre Vellino ISBN 0-673-18659-8
A web site in England using WIN-PROLOG
Related links and web page URLs and R&D related to U.S. Pat. Nos. 6,101,490 and 6,269,356.